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Time-clustering behavior and cycles in the time dynamics of car accident sequences in Lebanon

Author

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  • Ghandour, Ali J.
  • Lovallo, Michele
  • Telesca, Luciano

Abstract

This manuscript analyzes the temporal properties of sequences of car accidents in Lebanon from 2015 to 2018, using data from the Lebanese Road Accident Platform (LRAP). The Allan Factor that is a well suited methodology for investigating the time-clustering in point processes, revealed that the car accidents occurred over the whole Lebanese territory are characterized by a significant scaling behavior for timescales larger than about 2 weeks, with a clear cyclic component at 1 day. The analysis performed on car accident sequences in some specific areas of Lebanon revealed the presence of cycles varying from 1 day to 2 weeks as a function of the distance from Beirut, the capital city of Lebanon.

Suggested Citation

  • Ghandour, Ali J. & Lovallo, Michele & Telesca, Luciano, 2019. "Time-clustering behavior and cycles in the time dynamics of car accident sequences in Lebanon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 178-184.
    • Handle: RePEc:eee:phsmap:v:516:y:2019:i:c:p:178-184
    DOI: 10.1016/j.physa.2018.10.036
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    Cited by:

    1. Ghandour, Ali J. & Hammoud, Huda & Dimassi, Mohammad & Krayem, Houssam & Haydar, Jamal & Issa, Adam, 2020. "Allometric scaling of road accidents using social media crowd-sourced data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    2. Ali J. Ghandour & Huda Hammoud & Samar Al-Hajj, 2020. "Analyzing Factors Associated with Fatal Road Crashes: A Machine Learning Approach," IJERPH, MDPI, vol. 17(11), pages 1-13, June.
    3. Ghandour, Ali J. & Hammoud, Huda & Telesca, Luciano, 2019. "Transportation hazard spatial analysis using crowd-sourced social network data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 309-316.

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